My research focuses on methods to increase the efficiency of the sampling of conformational space during molecular dynamics (MD) simulations. Such sampling is critical for many applications of MD, specifically including (but not limited to) the calculation of free energy differences due to chemical or conformational changes in a molecule as well as prediction of the three-dimensional structure of biological molecules. My current work focuses on these two areas. I have performed simulations to calculate the relative solvation free energy between a series of substituted benzene molecules using the standard methods available in the AMBER suite of programs. Currently, I am implementing the Locally Enhanced Sampling (LES) method in AMBER, and I plan to repeat the calculations using LES, determining the relative benefits that can be obtained as well as the computational overhead. Additionally, I am investigating possible methods to improve the ability of MD simulations to predict the conformation of biological molecules in solution. Most such predictions are severely restricted by the limited conformational sampling that can occur during affordable simulations. I have therefore also implemented the LES method into the MD portion of AMBER, and I am currently running extensive tests to judge the performance. I am using LES both alone and in combination with Simulated Annealing (SA), comparing the results from simulations of small peptides in solution to those obtained by conventional MD simulations.